def growth_wheat():
seq, weather = sample_weather()
wdata = weather.get_weather(seq)
nsect = 1 #the number of element per leaf
adel = AdelWheat(nsect=nsect, nplants=1, seed=2)
# age=900に固定
g = adel.setup_canopy(900)
adel.grow(g, wdata)
# csv保存
with open('label.csv', 'w') as f:
writer = csv.writer(f)
label = g.property('label')
geometry = g.property('geometry')
is_green = g.property('is_green')
writer.writerow([label])
writer.writerow([geometry])
writer.writerow([is_green])
f.close()
# 茎，緑葉，茶葉，全体を生成して保存
for i in range(0, 4, 1):
st = plot3d1(g, i)
for t in range(len(st)):
st[t].name = str(t)
# 自動的に.mtlも保存してくれるっぽい
st.save("./" + "compare/" + str(i) + "/nsect" + str(nsect) + ".obj")
st = plot3d1(g, 4)
w = obj.ObjCodec()
w.write2("./compare/1/aa.obj", st)
def test_statistics():
nplants = 1
adel = AdelWheat(nplants=nplants)
g = adel.setup_canopy(age=100)
areas = adel.get_exposed_areas(g)
assert 'green_area' in areas
pstats = adel.plot_statistics(g)
def growth_wheat_someage():
seq, weather = sample_weather()
wdata = weather.get_weather(seq)
nsect = 1 #the number of element per leaf
adel = AdelWheat(nsect=nsect, nplants=1, seed=2)
# save_dir = './obj'
# save_dir = '/home/demo/document/ykato_git/datasets/omg_instance_segmentation/dataset_ver4/obj'
if os.name == 'nt':
save_dir = 'I:/ykato_git/datasets/omg_instance_segmentation/dataset_ver4/obj'
else:
save_dir = '/home/demo/document/ykato_git/datasets/omg_instance_segmentation/dataset_ver4/obj'
makeDirectory(save_dir)
for age in range(100, 1100, 100):
g = adel.setup_canopy(age)
adel.grow(g, wdata)
# パラメータcsv保存
with open(save_dir + '/param_age{}.csv'.format(age), 'w') as f:
writer = csv.writer(f)
label = g.property('label')
geometry = g.property('geometry')
is_green = g.property('is_green')
writer.writerow([label])
writer.writerow([geometry])
writer.writerow([is_green])
f.close()
# 茎，緑葉，茶葉，全体, 葉を生成して保存
folder_name = [
'all', 'stem', 'leaf', 'green_stem', 'green_leaf', 'brown_stem',
'brown_leaf'
]
for i in range(len(folder_name)):
makeDirectory(save_dir + '/' + folder_name[i] + '_age' + str(age))
st = plot3d1(g, i)
for t in range(len(st)):
st[t].name = str(t)
# 自動的に.mtlも保存してくれるっぽい
st.save(save_dir + '/' + folder_name[i] + '_age' + str(age) +
'.obj')
# if i != 3:
w = obj.ObjCodec()
w.write2(save_dir + '/' + folder_name[i] + '_age' + str(age), st)
def test_star():
wheat = AdelWheat()
g, _ = new_canopy(wheat, age=100)
geom = g.property('geometry')
rain_star, rain_exposed_area = caribu_star(geom)
light_star, light_exposed_area = caribu_star(geom, '16')
return rain_star, rain_exposed_area, light_star, light_exposed_area
# Create our own emitting lesion for this example
class LesionTutoDispersal(Lesion):
def __init__(self, mutable=False):
super(LesionTutoDispersal, self).__init__()
self.fungus_name = fungus_name
def emission(*args, **kwds):
return 10000
fungus = Fungus(Lesion=LesionTutoDispersal, parameters={"name": fungus_name})
source_lesion = fungus.lesion()
# create wheat canopy
adel = AdelWheat(nplants=20, nsect=7)
g = adel.setup_canopy(1500)
# plot
# adel.plot(g)
# choose source leaf
leaf_ids = [
id for id, label in g.property("label").iteritems()
if label.startswith("LeafElement")
]
source_leaf = g.node(leaf_ids[1])
# Alternatively, pick a leaf based on ist position in the canopy
vid, hmax = get_source_leaf_and_max_height(g)
source_leaf = g.node(vid)
def growth_wheat_someage():
seq, weather = sample_weather()
wdata = weather.get_weather(seq)
nsect = 1 #the number of element per leaf
for sed in range(100):
adel = AdelWheat(nsect=nsect, nplants=1, seed=sed)
# save_dir = './obj'
# save_dir = '/home/demo/document/ykato_git/datasets/omg_instance_segmentation/dataset_ver4/obj'
if os.name == 'nt':
save_dir = 'I:/ykato_git/datasets/omg_instance_segmentation/dataset_simulate_100/{}'.format(
sed)
else:
save_dir = '/home/demo/document/ykato_git/datasets/omg_instance_segmentation/dataset_ver4/obj'
makeDirectory(save_dir)
for age in range(100, 1100, 100):
g = adel.setup_canopy(age)
adel.grow(g, wdata)
# パラメータcsv保存
with open(save_dir + '/param_age{}.csv'.format(age), 'w') as f:
# writer=csv.writer(f)
label = [g.property('label')]
geometry = [g.property('geometry')]
is_green = [g.property('is_green')]
# writer.writerow([label])
# writer.writerow([geometry])
# writer.writerow([is_green])
header = label[0].keys()
writer = csv.DictWriter(f, header)
# header_row = {'j':k for k in header}
writer.writeheader()
for row in label:
writer.writerow(row)
header = geometry[0].keys()
writer = csv.DictWriter(f, header)
# header_row = {'k':k for k in header}
# writer.writerow(header_row)
writer.writeheader()
for row in geometry:
writer.writerow(row)
header = is_green[0].keys()
writer = csv.DictWriter(f, header)
# header_row = {'k':k for k in header}
# writer.writerow(header_row)
writer.writeheader()
for row in is_green:
writer.writerow(row)
# 茎，緑葉，茶葉，全体, 葉を生成して保存
folder_name = [
'all', 'stem', 'leaf', 'green_stem', 'green_leaf',
'brown_stem', 'brown_leaf'
]
for i in range(len(folder_name)):
makeDirectory(save_dir + '/' + folder_name[i] + '_age' +
str(age))
st = plot3d1(g, i)
for t in range(len(st)):
st[t].name = str(t)
# 自動的に.mtlも保存してくれるっぽい
st.save(save_dir + '/' + folder_name[i] + '_age' + str(age) +
'.obj')
# if i != 3:
w = obj.ObjCodec()
w.write2(save_dir + '/' + folder_name[i] + '_age' + str(age),
st)
def alep_custom_reconstructions(variety='Tremie13',
nplants=30,
sowing_density=250.,
plant_density=250.,
inter_row=0.15,
nsect=7,
seed=1,
scale_HS=1,
scale_leafDim_length=1,
scale_leafDim_width=1,
scale_leafRate=1,
scale_stemDim=1,
scale_stemRate=1,
scale_fallingRate=1,
scale_leafSenescence=1,
scale_tillering=1,
**kwds):
parameters = reconstruction_parameters()
stand = AgronomicStand(sowing_density=sowing_density,
plant_density=plant_density,
inter_row=inter_row,
noise=0.04,
density_curve_data=None)
n_emerged = nplants
MS_leaves_number_probabilities = {'11': 0.3, '12': 0.7}
tiller_proba = {'T1': 1., 'T2': 0.5, 'T3': 0.5, 'T4': 0.3}
ears_per_plant = 2.5
if 'tiller_probability' in kwds:
tiller_proba = {
k: min(1, p * kwds['tiller_probability'])
for k, p in tiller_proba.iteritems()
}
if 'proba_main_nff' in kwds:
MS_leaves_number_probabilities = {
'11': 1 - kwds['proba_main_nff'],
'12': kwds['proba_main_nff']
}
# scale _tillering
tiller_proba = {
k: min(1, p * scale_tillering)
for k, p in tiller_proba.iteritems()
}
em = pgen_ext.TillerEmission(primary_tiller_probabilities=tiller_proba)
reg = pgen_ext.TillerRegression(ears_per_plant=ears_per_plant *
scale_tillering)
#generate plants
HSfit = HS_fit()[variety]
axp = pgen_ext.AxePop(
MS_leaves_number_probabilities=MS_leaves_number_probabilities,
Emission=em,
Regression=reg,
std_em=HSfit.std_TT_hs_0)
plants = axp.plant_list(n_emerged)
# Measure and save Green leaf durations on the reference
adel_pars = parameters['adel_pars']
HSfit.mean_nff = axp.mean_nff()
Dimfit = dimension_fits(HS_fit(), **parameters)[variety]
GLfit = GL_fits(HS_fit(), **parameters)[variety]
pgen = pgen_ext.PlantGen(HSfit=HSfit,
GLfit=GLfit,
Dimfit=Dimfit,
adel_pars=adel_pars)
axeT, dimT, phenT = pgen.adelT(plants)
axeT = axeT.sort(['id_plt', 'id_cohort', 'N_phytomer'])
GreenDuration1_ref = axeT['TT_sen_phytomer1'] - axeT['TT_em_phytomer1']
phenT = phenT.sort(['id_phen', 'index_phytomer'])
dTTsen_ref = phenT['dTT_sen_phytomer']
dTTem_ref = phenT['dTT_em_phytomer']
# Modify fits
# HS_fit
# petit commentaire : scale_HS determine ligulation rate + emergence rate
# la duree emergence-ligulation est impactee du fait de ce changement (inevitable si on impose leaf_rate)
# mais aussi en raison de scale_leafRate(non souhaite => compensation ci dessous)
HS_ref = HSfit.a_cohort
leafDuration_ref = adel_pars['leafDuration']
HSfit.a_cohort /= scale_HS
# on compense en decalant l'emergence des plante
HSfit.TT_hs_0 += (1 -
adel_pars['fracLeaf']) / HS_ref * leafDuration_ref * (
float(scale_HS) / scale_leafRate - 1)
# Modify leaf dimension and growth rate
adel_pars['leafDuration'] = ((scale_leafDim_length*scale_leafDim_width) / scale_HS)* \
(leafDuration_ref / scale_leafRate)
Dimfit.scale['L_blade'] *= scale_leafDim_length
Dimfit.scale['W_blade'] *= scale_leafDim_width
# Modify stem dimension and growth rate
stemDuration_ref = adel_pars['stemDuration']
adel_pars['stemDuration'] = (scale_stemDim / scale_HS)* \
(stemDuration_ref / scale_stemRate)
Dimfit.scale['L_internode'] *= scale_stemDim
# Scale GL : GL flag, bolting and start_senescence : apply factor
# TEST EXTREME WITH LEAF RATE
#GLfit.GL_bolting *= scale_leafSenescence
#GLfit.GL_flag *= scale_leafSenescence
#GLfit.n0 *= scale_leafSenescence
# Modify green leaf durations and falling rate
pgen = pgen_ext.PlantGen(HSfit=HSfit,
GLfit=GLfit,
Dimfit=Dimfit,
adel_pars=adel_pars)
axeT, dimT, phenT = pgen.adelT(plants)
axeT = axeT.sort(['id_plt', 'id_cohort', 'N_phytomer'])
phenT = phenT.sort(['id_phen', 'index_phytomer'])
# Modify senescence
axeT['TT_sen_phytomer1'] = axeT[
'TT_em_phytomer1'] + scale_leafSenescence * GreenDuration1_ref
phenT['dTT_sen_phytomer'] = dTTsen_ref + (phenT['dTT_em_phytomer'] -
dTTem_ref)
devT = devCsv(axeT, dimT, phenT)
leaves = leafshape_fits(**parameters)[variety]
bins_ref = leaves.bins
bins_ref[-1] = 21.
bins = [
x * scale_HS / scale_fallingRate if i_x != 0 else x * scale_HS
for i_x, x in enumerate(bins_ref)
]
leaves.bins = bins
return AdelWheat(nplants=nplants,
nsect=nsect,
devT=devT,
stand=stand,
seed=seed,
sample='sequence',
leaves=leaves,
run_adel_pars=adel_pars)
fungus_name = "lesion_tutorial"
# Create our own emitting lesion for this example
class LesionTutoDispersal(Lesion):
def __init__(self, mutable=False):
super(LesionTutoDispersal, self).__init__()
self.fungus_name = fungus_name
def emission(*args, **kwds):
return 10000
fungus = Fungus(Lesion=LesionTutoDispersal, parameters={"name":fungus_name})
source_lesion = fungus.lesion()
# create wheat canopy
adel= AdelWheat(nplants=20, nsect=7)
g = adel.setup_canopy(1500)
# plot
# adel.plot(g)
# choose source leaf
leaf_ids = [id for id, label in g.property("label").iteritems() if label.startswith("LeafElement")]
source_leaf = g.node(leaf_ids[1])
# Alternatively, pick a leaf based on ist position in the canopy
vid, hmax = get_source_leaf_and_max_height(g)
source_leaf = g.node(vid)
# inoculate this leaf
source_lesion.is_sporulating = True # Required for Popdrops usage
source_leaf.lesions = [source_lesion]
def test_static(age=100):
nplants = 1
adel = AdelWheat(nplants=nplants)
g = adel.setup_canopy(age=100)
assert len(g.vertices()) > 20
assert g.property('geometry').values()[0].isValid()
from alinea.adel.astk_interface import AdelWheat from alinea.astk.Weather import sample_weather seq, weather = sample_weather() wdata = weather.get_weather(seq) adel = AdelWheat(nsect=2) g = adel.setup_canopy(100) adel.grow(g, wdata)
mesh = mesh.geometry
if colors:
shape = Shape(mesh, Material(Color3(* colors.get(vid, [0,0,0]) )))
shape.id = vid
scene.add(shape)
for vid, mesh in geometries.iteritems():
geom2shape(vid, mesh, scene)
pgl.Viewer.display(scene)
return scene
# 1. Get a sample scene from adel and create a mtg
adel = AdelWheat()
g = adel.setup_canopy(600)
# 2. Run light with default PARs (quickest call)
geom = g.property('geometry')
light_star, light_exposed_area = caribu_star(geom)
# 3. Update mtg with light_star
g.properties()['light_star'] = light_star
# 4. Add a color property to the mtg and view the result on a plot 3D
g = colormap(g, 'light_star', cmap='jet', lognorm=True)
plot3d(g)
# 5. Configure the light sources (zenith, side, diffuse)
from alinea.adel.astk_interface import AdelWheat from alinea.astk.Weather import sample_weather seq, weather = sample_weather() wdata = weather.get_weather(seq) adel = AdelWheat(nsect=2) g = adel.setup_canopy(100) adel.grow(g, wdata)
def test_rain_and_light():
wheat = AdelWheat()
g, _ = new_canopy(wheat, age=100)
rain_and_light_star(g)
return g
from alinea.caribu.caribu_star import *
from alinea.adel.astk_interface import AdelWheat
from alinea.astk.plant_interface import *
from alinea.astk.plantgl_utils import *
wheat = AdelWheat()
g,_ = new_canopy(wheat, age=550)
geom = g.property('geometry')
areas, normals = get_area_and_normal(geom)
energie, emission, direction, elevation, azimuth = turtle.turtle(sectors=1, energy=1)
sources = zip(energie,direction)
out = run_caribu(sources, geom, output_by_triangle=False)
rain_fraction, rain_exposition = exposed_surface(geom)
light_fraction, light_exposition = exposed_surface(geom, '16')
#one mature length
leaf_id=32
elt_id = 34
#leaf_id=8
#elt_id = 10
length = g[leaf_id]['length']
vlength = g[leaf_id]['visible_length']
w=g[leaf_id]['shape_max_width']
area_adel = g[elt_id]['area']
area_pgl = sum(areas[elt_id])
area_caribu = out['Area'][elt_id]
area_exposition = rain_exposition[elt_id] / rain_fraction[elt_id] /0.01**2
print area_adel, area_pgl, area_caribu, area_exposition
